Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting

The smart metering infrastructure has changed how electricity is measured in both residential and industrial application. The large amount of data collected by smart meter per day provides a huge potential for analytics to support the operation of a smart grid, an example of which is energy demand forecasting. Short term energy forecasting can be used by utilities to assess if any forecasted peak energy demand would have an adverse effect on the power system transmission and distribution infrastructure. It can also help in load scheduling and demand side management. Many techniques have been proposed to forecast time series including Support Vector Machine, Artificial Neural Network and Deep Learning. In this work we use Long Short Term Memory architecture to forecast 3-day ahead energy demand across each month in the year. The results show that 3-day ahead demand can be accurately forecasted with a Mean Absolute Percentage Error of 3.15%. In addition to that, the paper proposes way to quantify the time as a feature to be used in the training phase which is shown to affect the network performance

A Noval Approach towards Academic Data Sharing on Cloud Environment Using File Synchronization

Nowadays the use of cloud computing is increased rapidly. The Cloud computing is very much important in the data sharing application. Due to increased use of cloud platform the management of the file problem on the cloud is increased for every single day the data is uploaded on to the cloud. So increasing demand of computation on a processing of file transfer leads to develop a new kind of technology that provides services for the manageable way. This manageable way is achieved by using file synchronization techniques in the cloud environment. Cloud computing usually consists of front-end user devices and back-end cloud servers. This gives users to access a large volume of storage on the cloud. In this project, the user can upload a file from PC (and from mobile as well) on to the cloud storage. These files will be automatically synchronized on to the user's device. So, the user can be viewed the file from anywhere and on any device. In the existing system, we need to download files manually. This paradigm provides the user to synchronize data automatically between devices. Therefore, we are implementing this paradigm for windows platform only. Here we are demonstrating this concept by using simple assignment and notes sharing application between teachers and students

Stress effects on work efficiency: study by professionals at the Cambridge school library of Karachi Sindh, Pakistan.

Librarians, like other professionals, face stress from a diversity of sources around the world. A population of 70 Cambridge school library professionals was studied to see if there was a significant relation between work efficiency and occupational stress. This research study is investigated on the relation of school library professionals working in Karachi\u27s Cambridge schools on Stress at work and work efficiency. The main purpose of this research was to identify the level of occupational stress among school librarians, as well as gender and marital status disparities in occupational stress and work efficiency among school librarians, as well as the consequences of occupational stress on efficiency from work. For this investigation, a survey research strategy was carried out. Census/enumerative techniques was adapted. The sample size of the study was 70, response rate was 60 (87%) and the remaining 10 (13%) did not respond. A questionnaire was used to collect primary data and consisted of close ended queries to measure the information. Cronbach’s Alpha used to check the reliability of the questionnaire. All five hypothesis tested t value and simple linear regression collected data were analyzed by SPSS ver. 22 software. According to the bases of the findings, working in school libraries generates a lot of occupational overload. There was no significant mean difference in the perception of work stress of male and female library professionals (p\u3e0.05), however there was a significant mean difference in the perception of work efficiency of male and female library professionals (p\u3e0.05). \u3e0.05). On seven work efficiency characteristics, men outperformed women: interpersonal relationships with colleagues, ability to handle multiple jobs, communication skills, punctuality and regularity at work, technical skills, problem solving, and quality of library work. When it came to the relationship between occupational stress and performance and performance at work (r=0.0624, p\u3e0.01), the outcome showed a significant relationship (r=0.0624, p\u3e0.01). In addition, roll ambiguity, overload, conflict and career stagnation were some of the factors that negatively impacted the professional performance of school library professionals. The results demonstrated a small but statistically significant negative association between occupational stress and work efficiency, implying that a rise in occupational stress has a detrimental impact on the gender and marital status of school library professionals\u27 work efficiency. Four hypothesis are rejected based on t value analysis, but the fifth is supported based on t value and simple linear regression. This study found that the factors that contributing to work stress is significant with school library professional’s performance and it also concluded that the employees at Cambridge schooling system were experiencing occupational stress

The HIV-1 Nef protein binds argonaute-2 and functions as a viral suppressor of RNA interference

The HIV-1 accessory protein Nef is an important virulence factor. It associates with cellular membranes and modulates the endocytic machinery and signaling pathways. Nef also increases the proliferation of multivesicular bodies (MVBs), which are sites for virus assembly and budding in macrophages. The RNA interference (RNAi) pathway proteins Ago2 and GW182 localize to MVBs, suggesting these to be sites for assembly and turnover of the miRNA-induced silencing complex (miRISC). While RNAi affects HIV replication, it is not clear if the virus encodes a suppressor activity to overcome this innate host response. Here we show that Nef colocalizes with MVBs and binds Ago2 through two highly conserved Glycine-Tryptophan (GW) motifs, mutations in which abolish Nef binding to Ago2 and reduce virus yield and infectivity. Nef also inhibits the slicing activity of Ago2 and disturbs the sorting of GW182 into exosomes resulting in the suppression of miRNA-induced silencing. Thus, besides its other activities, the HIV-1 Nef protein is also proposed to function as a viral suppressor of RNAi (VSR)

British South Asian ancestry participants views of pharmacogenomics clinical implementation and research: a thematic analysis.

BACKGROUND: South Asian ancestry populations are underrepresented in genomic studies and therapeutics trials. British South Asians suffer from multi-morbidity leading to polypharmacy. Our objective was to elucidate British South Asian ancestry community perspectives on pharmacogenomic implementation and sharing pharmacogenomic clinical data for research. METHODS: Four focus groups were conducted (9-12 participants in each). Two groups were mixed gender, while one group was male only and one was female only. Simultaneous interpretation was available to participants in Urdu and Bengali. Focus groups were recorded and abridged transcription and thematic analysis were undertaken. RESULTS: There were 42 participants, 64% female. 26% were born in the UK or Europe. 52% were born in Bangladesh and 17% in Pakistan. 36% reported university level education. Implementation of pharmacogenomics was perceived to be beneficial to individuals but pose a risk of overburdening resource limited systems. Pharmacogenomic research was perceived to be beneficial to the community, with concerns about data privacy and misuse. Data sharing was desirable if the researchers did not have a financial stake, and benefits would be shared. Trust was the key condition for the acceptability of both clinical implementation and research. Trust was linked with medication compliance. Education, outreach, and communication facilitate trust. CONCLUSIONS (SIGNIFICANCE AND IMPACT OF THE STUDY): Pharmacogenomics implementation with appropriate education and communication has the potential to enhance trust and contribute to increased medication compliance. Trust drives data sharing, which would enable enhanced representation in research. Representation in scientific evidence base could cyclically enhance trust and compliance

Assessing cloud QoS predictions using OWA in neural network methods

Quality of Service (QoS) is the key parameter to measure the overall performance of service-oriented applications. In a myriad of web services, the QoS data has multiple highly sparse and enormous dimensions. It is a great challenge to reduce computational complexity by reducing data dimensions without losing information to predict QoS for future intervals. This paper uses an Induced Ordered Weighted Average (IOWA) layer in the prediction layer to lessen the size of a dataset and analyse the prediction accuracy of cloud QoS data. The approach enables stakeholders to manage extensive QoS data better and handle complex nonlinear predictions. The paper evaluates the cloud QoS prediction using an IOWA operator with nine neural network methods—Cascade-forward backpropagation, Elman backpropagation, Feedforward backpropagation, Generalised regression, NARX, Layer recurrent, LSTM, GRU and LSTM-GRU. The paper compares results using RMSE, MAE, and MAPE to measure prediction accuracy as a benchmark. A total of 2016 QoS data are extracted from Amazon EC2 US-West instance to predict future 96 intervals. The analysis results show that the approach significantly decreases the data size by 66%, from 2016 to 672 records with improved or equal accuracy. The case study demonstrates the approach's effectiveness while handling complexity, reducing data dimension with better prediction accuracy

Population‐based cohort study of outcomes following cholecystectomy for benign gallbladder diseases

Background The aim was to describe the management of benign gallbladder disease and identify characteristics associated with all‐cause 30‐day readmissions and complications in a prospective population‐based cohort. Methods Data were collected on consecutive patients undergoing cholecystectomy in acute UK and Irish hospitals between 1 March and 1 May 2014. Potential explanatory variables influencing all‐cause 30‐day readmissions and complications were analysed by means of multilevel, multivariable logistic regression modelling using a two‐level hierarchical structure with patients (level 1) nested within hospitals (level 2). Results Data were collected on 8909 patients undergoing cholecystectomy from 167 hospitals. Some 1451 cholecystectomies (16·3 per cent) were performed as an emergency, 4165 (46·8 per cent) as elective operations, and 3293 patients (37·0 per cent) had had at least one previous emergency admission, but had surgery on a delayed basis. The readmission and complication rates at 30 days were 7·1 per cent (633 of 8909) and 10·8 per cent (962 of 8909) respectively. Both readmissions and complications were independently associated with increasing ASA fitness grade, duration of surgery, and increasing numbers of emergency admissions with gallbladder disease before cholecystectomy. No identifiable hospital characteristics were linked to readmissions and complications. Conclusion Readmissions and complications following cholecystectomy are common and associated with patient and disease characteristics